Overview

Brought to you by YData

Dataset statistics

Number of variables13
Number of observations173
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.9 KiB
Average record size in memory112.0 B

Variable types

Numeric13

Alerts

Alcohol is highly overall correlated with Color_Intensity and 1 other fieldsHigh correlation
Color_Intensity is highly overall correlated with AlcoholHigh correlation
Flavanoids is highly overall correlated with Hue and 4 other fieldsHigh correlation
Hue is highly overall correlated with Flavanoids and 1 other fieldsHigh correlation
Magnesium is highly overall correlated with ProlineHigh correlation
Malic_Acid is highly overall correlated with HueHigh correlation
Nonflavanoid_Phenols is highly overall correlated with FlavanoidsHigh correlation
OD280 is highly overall correlated with Flavanoids and 2 other fieldsHigh correlation
Proanthocyanins is highly overall correlated with Flavanoids and 2 other fieldsHigh correlation
Proline is highly overall correlated with Alcohol and 1 other fieldsHigh correlation
Total_Phenols is highly overall correlated with Flavanoids and 2 other fieldsHigh correlation

Reproduction

Analysis started2025-05-23 14:59:12.454237
Analysis finished2025-05-23 14:59:33.743227
Duration21.29 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Alcohol
Real number (ℝ)

High correlation 

Distinct124
Distinct (%)71.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.989769
Minimum11.03
Maximum14.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:33.878322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum11.03
5-th percentile11.656
Q112.34
median13.05
Q313.67
95-th percentile14.224
Maximum14.83
Range3.8
Interquartile range (IQR)1.33

Descriptive statistics

Standard deviation0.81350373
Coefficient of variation (CV)0.062626498
Kurtosis-0.84731589
Mean12.989769
Median Absolute Deviation (MAD)0.68
Skewness-0.03586676
Sum2247.23
Variance0.66178832
MonotonicityNot monotonic
2025-05-23T14:59:34.046521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.05 6
 
3.5%
12.37 5
 
2.9%
12.08 5
 
2.9%
12.29 4
 
2.3%
12.42 3
 
1.7%
12.25 3
 
1.7%
12 3
 
1.7%
13.5 2
 
1.2%
13.86 2
 
1.2%
13.71 2
 
1.2%
Other values (114) 138
79.8%
ValueCountFrequency (%)
11.03 1
0.6%
11.41 1
0.6%
11.45 1
0.6%
11.46 1
0.6%
11.56 1
0.6%
11.61 1
0.6%
11.62 1
0.6%
11.64 1
0.6%
11.65 1
0.6%
11.66 1
0.6%
ValueCountFrequency (%)
14.83 1
0.6%
14.75 1
0.6%
14.39 1
0.6%
14.38 2
1.2%
14.37 1
0.6%
14.34 1
0.6%
14.3 1
0.6%
14.23 1
0.6%
14.22 2
1.2%
14.2 1
0.6%

Malic_Acid
Real number (ℝ)

High correlation 

Distinct129
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3309249
Minimum0.74
Maximum5.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:34.274920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.74
5-th percentile1.046
Q11.61
median1.86
Q33.03
95-th percentile4.498
Maximum5.8
Range5.06
Interquartile range (IQR)1.42

Descriptive statistics

Standard deviation1.118356
Coefficient of variation (CV)0.47979066
Kurtosis0.36170118
Mean2.3309249
Median Absolute Deviation (MAD)0.51
Skewness1.0674935
Sum403.25
Variance1.2507201
MonotonicityNot monotonic
2025-05-23T14:59:34.482993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.73 7
 
4.0%
1.67 4
 
2.3%
1.81 4
 
2.3%
1.51 3
 
1.7%
1.35 3
 
1.7%
1.68 3
 
1.7%
1.53 3
 
1.7%
1.61 3
 
1.7%
1.9 3
 
1.7%
1.71 2
 
1.2%
Other values (119) 138
79.8%
ValueCountFrequency (%)
0.74 1
0.6%
0.89 1
0.6%
0.9 1
0.6%
0.92 1
0.6%
0.94 2
1.2%
0.98 1
0.6%
0.99 1
0.6%
1.01 1
0.6%
1.07 1
0.6%
1.09 1
0.6%
ValueCountFrequency (%)
5.8 1
0.6%
5.65 1
0.6%
5.51 1
0.6%
5.19 1
0.6%
5.04 1
0.6%
4.95 1
0.6%
4.72 1
0.6%
4.61 1
0.6%
4.6 1
0.6%
4.43 1
0.6%

Ash
Real number (ℝ)

Distinct78
Distinct (%)45.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3636994
Minimum1.36
Maximum3.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:34.664910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.36
5-th percentile1.92
Q12.21
median2.36
Q32.54
95-th percentile2.744
Maximum3.23
Range1.87
Interquartile range (IQR)0.33

Descriptive statistics

Standard deviation0.27339205
Coefficient of variation (CV)0.11566278
Kurtosis1.2511441
Mean2.3636994
Median Absolute Deviation (MAD)0.16
Skewness-0.15044751
Sum408.92
Variance0.074743211
MonotonicityNot monotonic
2025-05-23T14:59:34.873323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.3 7
 
4.0%
2.28 7
 
4.0%
2.36 6
 
3.5%
2.32 6
 
3.5%
2.38 5
 
2.9%
2.48 5
 
2.9%
2.2 5
 
2.9%
2.4 4
 
2.3%
2.1 4
 
2.3%
2.62 4
 
2.3%
Other values (68) 120
69.4%
ValueCountFrequency (%)
1.36 1
0.6%
1.7 2
1.2%
1.71 1
0.6%
1.75 1
0.6%
1.82 1
0.6%
1.88 1
0.6%
1.9 1
0.6%
1.92 2
1.2%
1.94 1
0.6%
1.95 1
0.6%
ValueCountFrequency (%)
3.23 1
0.6%
3.22 1
0.6%
2.92 1
0.6%
2.87 1
0.6%
2.86 1
0.6%
2.84 1
0.6%
2.8 1
0.6%
2.78 1
0.6%
2.75 1
0.6%
2.74 2
1.2%

Ash_Alcanity
Real number (ℝ)

Distinct61
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.496532
Minimum10.6
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:35.104793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10.6
5-th percentile14.72
Q117.2
median19.5
Q321.5
95-th percentile25
Maximum30
Range19.4
Interquartile range (IQR)4.3

Descriptive statistics

Standard deviation3.3618222
Coefficient of variation (CV)0.17243181
Kurtosis0.47674389
Mean19.496532
Median Absolute Deviation (MAD)2.1
Skewness0.2211198
Sum3372.9
Variance11.301848
MonotonicityNot monotonic
2025-05-23T14:59:35.311913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 15
 
8.7%
16 11
 
6.4%
18 10
 
5.8%
21 10
 
5.8%
19 9
 
5.2%
21.5 8
 
4.6%
19.5 7
 
4.0%
22 7
 
4.0%
18.5 7
 
4.0%
22.5 6
 
3.5%
Other values (51) 83
48.0%
ValueCountFrequency (%)
10.6 1
0.6%
11.2 1
0.6%
11.4 1
0.6%
12 1
0.6%
12.4 1
0.6%
13.2 1
0.6%
14 2
1.2%
14.6 1
0.6%
14.8 1
0.6%
15 2
1.2%
ValueCountFrequency (%)
30 1
 
0.6%
28.5 2
 
1.2%
27 1
 
0.6%
26.5 1
 
0.6%
26 1
 
0.6%
25.5 1
 
0.6%
25 5
2.9%
24.5 3
1.7%
24 5
2.9%
23.6 1
 
0.6%

Magnesium
Real number (ℝ)

High correlation 

Distinct53
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.722543
Minimum70
Maximum162
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:35.518046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile81.6
Q188
median98
Q3107
95-th percentile124.8
Maximum162
Range92
Interquartile range (IQR)19

Descriptive statistics

Standard deviation14.311055
Coefficient of variation (CV)0.14350872
Kurtosis2.1780585
Mean99.722543
Median Absolute Deviation (MAD)10
Skewness1.1370019
Sum17252
Variance204.80629
MonotonicityNot monotonic
2025-05-23T14:59:35.740480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88 13
 
7.5%
86 11
 
6.4%
98 9
 
5.2%
101 8
 
4.6%
96 7
 
4.0%
102 7
 
4.0%
85 6
 
3.5%
94 6
 
3.5%
112 6
 
3.5%
89 5
 
2.9%
Other values (43) 95
54.9%
ValueCountFrequency (%)
70 1
 
0.6%
78 2
 
1.2%
80 5
 
2.9%
81 1
 
0.6%
82 1
 
0.6%
84 3
 
1.7%
85 6
3.5%
86 11
6.4%
87 3
 
1.7%
88 13
7.5%
ValueCountFrequency (%)
162 1
0.6%
151 1
0.6%
139 1
0.6%
136 1
0.6%
134 1
0.6%
132 1
0.6%
128 1
0.6%
127 1
0.6%
126 1
0.6%
124 1
0.6%

Total_Phenols
Real number (ℝ)

High correlation 

Distinct95
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2909249
Minimum0.98
Maximum3.88
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:35.955012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.98
5-th percentile1.38
Q11.74
median2.35
Q32.8
95-th percentile3.282
Maximum3.88
Range2.9
Interquartile range (IQR)1.06

Descriptive statistics

Standard deviation0.62762404
Coefficient of variation (CV)0.27396099
Kurtosis-0.82052929
Mean2.2909249
Median Absolute Deviation (MAD)0.51
Skewness0.10510117
Sum396.33
Variance0.39391193
MonotonicityNot monotonic
2025-05-23T14:59:36.192298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.2 8
 
4.6%
2.6 6
 
3.5%
2.8 6
 
3.5%
2.95 5
 
2.9%
3 5
 
2.9%
2 5
 
2.9%
2.45 4
 
2.3%
1.65 4
 
2.3%
1.38 4
 
2.3%
2.85 3
 
1.7%
Other values (85) 123
71.1%
ValueCountFrequency (%)
0.98 1
 
0.6%
1.1 1
 
0.6%
1.15 1
 
0.6%
1.25 1
 
0.6%
1.28 1
 
0.6%
1.3 1
 
0.6%
1.35 1
 
0.6%
1.38 4
2.3%
1.39 2
1.2%
1.4 2
1.2%
ValueCountFrequency (%)
3.88 1
 
0.6%
3.85 1
 
0.6%
3.52 1
 
0.6%
3.5 1
 
0.6%
3.4 1
 
0.6%
3.38 1
 
0.6%
3.3 3
1.7%
3.27 1
 
0.6%
3.25 2
1.2%
3.2 1
 
0.6%

Flavanoids
Real number (ℝ)

High correlation 

Distinct130
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0218497
Minimum0.34
Maximum5.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:36.415185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.34
5-th percentile0.556
Q11.2
median2.13
Q32.86
95-th percentile3.51
Maximum5.08
Range4.74
Interquartile range (IQR)1.66

Descriptive statistics

Standard deviation0.99816753
Coefficient of variation (CV)0.49369027
Kurtosis-0.86276993
Mean2.0218497
Median Absolute Deviation (MAD)0.83
Skewness0.051756889
Sum349.78
Variance0.99633842
MonotonicityNot monotonic
2025-05-23T14:59:36.600251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.03 3
 
1.7%
2.68 3
 
1.7%
0.58 3
 
1.7%
0.6 3
 
1.7%
2.65 3
 
1.7%
1.25 3
 
1.7%
2.17 2
 
1.2%
2.76 2
 
1.2%
2.43 2
 
1.2%
3.39 2
 
1.2%
Other values (120) 147
85.0%
ValueCountFrequency (%)
0.34 1
0.6%
0.47 2
1.2%
0.48 1
0.6%
0.49 1
0.6%
0.5 1
0.6%
0.51 1
0.6%
0.52 1
0.6%
0.55 1
0.6%
0.56 1
0.6%
0.57 1
0.6%
ValueCountFrequency (%)
5.08 1
0.6%
3.93 1
0.6%
3.75 1
0.6%
3.74 1
0.6%
3.69 1
0.6%
3.67 1
0.6%
3.64 1
0.6%
3.56 1
0.6%
3.54 1
0.6%
3.49 1
0.6%

Nonflavanoid_Phenols
Real number (ℝ)

High correlation 

Distinct39
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3632948
Minimum0.13
Maximum0.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:36.752607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.13
5-th percentile0.196
Q10.27
median0.34
Q30.44
95-th percentile0.6
Maximum0.66
Range0.53
Interquartile range (IQR)0.17

Descriptive statistics

Standard deviation0.1243266
Coefficient of variation (CV)0.34221961
Kurtosis-0.63479058
Mean0.3632948
Median Absolute Deviation (MAD)0.09
Skewness0.44092686
Sum62.85
Variance0.015457104
MonotonicityNot monotonic
2025-05-23T14:59:36.886144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0.26 11
 
6.4%
0.43 11
 
6.4%
0.29 9
 
5.2%
0.32 9
 
5.2%
0.4 8
 
4.6%
0.34 8
 
4.6%
0.37 8
 
4.6%
0.3 7
 
4.0%
0.27 7
 
4.0%
0.24 7
 
4.0%
Other values (29) 88
50.9%
ValueCountFrequency (%)
0.13 1
 
0.6%
0.14 2
 
1.2%
0.17 4
 
2.3%
0.19 2
 
1.2%
0.2 2
 
1.2%
0.21 6
3.5%
0.22 6
3.5%
0.24 7
4.0%
0.25 2
 
1.2%
0.26 11
6.4%
ValueCountFrequency (%)
0.66 1
 
0.6%
0.63 4
2.3%
0.61 3
1.7%
0.6 3
1.7%
0.58 3
1.7%
0.56 1
 
0.6%
0.55 1
 
0.6%
0.53 6
3.5%
0.52 5
2.9%
0.5 5
2.9%

Proanthocyanins
Real number (ℝ)

High correlation 

Distinct100
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5959538
Minimum0.41
Maximum3.58
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:37.024127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.41
5-th percentile0.73
Q11.25
median1.56
Q31.95
95-th percentile2.724
Maximum3.58
Range3.17
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.57174543
Coefficient of variation (CV)0.35824686
Kurtosis0.60242343
Mean1.5959538
Median Absolute Deviation (MAD)0.36
Skewness0.51697362
Sum276.1
Variance0.32689284
MonotonicityNot monotonic
2025-05-23T14:59:37.204073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.35 9
 
5.2%
1.46 7
 
4.0%
1.87 6
 
3.5%
1.25 4
 
2.3%
2.08 4
 
2.3%
1.98 4
 
2.3%
1.56 4
 
2.3%
1.95 3
 
1.7%
1.66 3
 
1.7%
1.97 3
 
1.7%
Other values (90) 126
72.8%
ValueCountFrequency (%)
0.41 1
 
0.6%
0.42 2
1.2%
0.55 1
 
0.6%
0.62 1
 
0.6%
0.64 2
1.2%
0.68 1
 
0.6%
0.73 2
1.2%
0.8 2
1.2%
0.81 1
 
0.6%
0.83 3
1.7%
ValueCountFrequency (%)
3.58 1
 
0.6%
3.28 1
 
0.6%
2.96 1
 
0.6%
2.91 2
1.2%
2.81 3
1.7%
2.76 1
 
0.6%
2.7 1
 
0.6%
2.5 1
 
0.6%
2.49 1
 
0.6%
2.45 1
 
0.6%

Color_Intensity
Real number (ℝ)

High correlation 

Distinct130
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0579191
Minimum1.28
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:37.877402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.28
5-th percentile2.104
Q13.17
median4.6
Q36.25
95-th percentile9.628
Maximum13
Range11.72
Interquartile range (IQR)3.08

Descriptive statistics

Standard deviation2.3507518
Coefficient of variation (CV)0.46476659
Kurtosis0.29214482
Mean5.0579191
Median Absolute Deviation (MAD)1.55
Skewness0.85775726
Sum875.02
Variance5.526034
MonotonicityNot monotonic
2025-05-23T14:59:38.011827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.6 4
 
2.3%
3.8 4
 
2.3%
2.8 3
 
1.7%
2.9 3
 
1.7%
5 3
 
1.7%
5.6 3
 
1.7%
4.5 3
 
1.7%
4.6 3
 
1.7%
3.4 3
 
1.7%
5.4 3
 
1.7%
Other values (120) 141
81.5%
ValueCountFrequency (%)
1.28 1
0.6%
1.74 1
0.6%
1.9 1
0.6%
1.95 2
1.2%
2 1
0.6%
2.06 2
1.2%
2.08 1
0.6%
2.12 1
0.6%
2.15 1
0.6%
2.2 1
0.6%
ValueCountFrequency (%)
13 1
0.6%
11.75 1
0.6%
10.8 1
0.6%
10.68 1
0.6%
10.52 1
0.6%
10.26 1
0.6%
10.2 1
0.6%
9.899999 1
0.6%
9.7 1
0.6%
9.58 1
0.6%

Hue
Real number (ℝ)

High correlation 

Distinct77
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.95673988
Minimum0.48
Maximum1.71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:38.169513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.48
5-th percentile0.57
Q10.78
median0.97
Q31.12
95-th percentile1.292
Maximum1.71
Range1.23
Interquartile range (IQR)0.34

Descriptive statistics

Standard deviation0.230318
Coefficient of variation (CV)0.24073209
Kurtosis-0.3580436
Mean0.95673988
Median Absolute Deviation (MAD)0.16
Skewness0.025942233
Sum165.516
Variance0.05304638
MonotonicityNot monotonic
2025-05-23T14:59:38.317816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.04 8
 
4.6%
1.23 7
 
4.0%
1.25 5
 
2.9%
1.12 5
 
2.9%
0.89 5
 
2.9%
0.57 5
 
2.9%
0.75 4
 
2.3%
0.96 4
 
2.3%
1.07 4
 
2.3%
1.09 4
 
2.3%
Other values (67) 122
70.5%
ValueCountFrequency (%)
0.48 1
 
0.6%
0.54 1
 
0.6%
0.55 1
 
0.6%
0.56 2
 
1.2%
0.57 5
2.9%
0.58 2
 
1.2%
0.59 2
 
1.2%
0.6 3
1.7%
0.61 2
 
1.2%
0.62 1
 
0.6%
ValueCountFrequency (%)
1.71 1
 
0.6%
1.45 1
 
0.6%
1.42 1
 
0.6%
1.38 1
 
0.6%
1.36 2
 
1.2%
1.33 1
 
0.6%
1.31 2
 
1.2%
1.28 2
 
1.2%
1.27 1
 
0.6%
1.25 5
2.9%

OD280
Real number (ℝ)

High correlation 

Distinct119
Distinct (%)68.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5993642
Minimum1.27
Maximum4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:38.454345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.27
5-th percentile1.45
Q11.92
median2.78
Q33.17
95-th percentile3.58
Maximum4
Range2.73
Interquartile range (IQR)1.25

Descriptive statistics

Standard deviation0.71229416
Coefficient of variation (CV)0.2740263
Kurtosis-1.103906
Mean2.5993642
Median Absolute Deviation (MAD)0.52
Skewness-0.28383341
Sum449.69
Variance0.50736297
MonotonicityNot monotonic
2025-05-23T14:59:38.612491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.87 5
 
2.9%
2.78 4
 
2.3%
3 4
 
2.3%
1.82 4
 
2.3%
2.77 3
 
1.7%
3.17 3
 
1.7%
2.96 3
 
1.7%
1.33 3
 
1.7%
1.75 3
 
1.7%
1.56 3
 
1.7%
Other values (109) 138
79.8%
ValueCountFrequency (%)
1.27 1
 
0.6%
1.29 2
1.2%
1.3 1
 
0.6%
1.33 3
1.7%
1.36 1
 
0.6%
1.42 1
 
0.6%
1.47 1
 
0.6%
1.48 1
 
0.6%
1.51 2
1.2%
1.55 1
 
0.6%
ValueCountFrequency (%)
4 1
0.6%
3.92 1
0.6%
3.82 1
0.6%
3.71 1
0.6%
3.69 1
0.6%
3.64 1
0.6%
3.63 1
0.6%
3.59 1
0.6%
3.58 2
1.2%
3.57 1
0.6%

Proline
Real number (ℝ)

High correlation 

Distinct120
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean743.50867
Minimum278
Maximum1680
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2025-05-23T14:59:38.746793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum278
5-th percentile353.8
Q1500
median672
Q3985
95-th percentile1301
Maximum1680
Range1402
Interquartile range (IQR)485

Descriptive statistics

Standard deviation314.96297
Coefficient of variation (CV)0.42361707
Kurtosis-0.19471369
Mean743.50867
Median Absolute Deviation (MAD)202
Skewness0.78923134
Sum128627
Variance99201.67
MonotonicityNot monotonic
2025-05-23T14:59:38.890764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
520 5
 
2.9%
680 5
 
2.9%
750 4
 
2.3%
630 4
 
2.3%
625 4
 
2.3%
1035 3
 
1.7%
480 3
 
1.7%
450 3
 
1.7%
562 3
 
1.7%
495 3
 
1.7%
Other values (110) 136
78.6%
ValueCountFrequency (%)
278 1
0.6%
290 1
0.6%
312 1
0.6%
315 1
0.6%
325 1
0.6%
342 1
0.6%
345 2
1.2%
352 1
0.6%
355 1
0.6%
365 1
0.6%
ValueCountFrequency (%)
1680 1
0.6%
1547 1
0.6%
1515 1
0.6%
1510 1
0.6%
1480 1
0.6%
1450 1
0.6%
1375 1
0.6%
1320 1
0.6%
1310 1
0.6%
1295 1
0.6%

Interactions

2025-05-23T14:59:32.165626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:13.208213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:15.961045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.531088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.929460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:20.639151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.042228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:23.938138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.465190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.713162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.018765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.289492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:30.899732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.262476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:13.410008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.081610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.637594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.053389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:20.741166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.199191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.052501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.582167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.818088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.124306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.380404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:30.995029image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.367971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:13.573272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.180626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.735186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.161041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:20.831053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.342520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.134526image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.669904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.915731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.222834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.469553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.089164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.464241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:13.745110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.294303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.834042image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.291080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:20.923888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.492857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.225004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.765269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.021883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.325457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.564652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.185984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.572445image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:13.947973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.425941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.948796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.403258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.018238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.637337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.328772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.864667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.134996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.434731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.671441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.294712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.661987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:14.144221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.765460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.065107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.500505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.105632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.771606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.417630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.950295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.234417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.523428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.764961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.391138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.761436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:14.343512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.861904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.197357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.608248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.199066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:22.899430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.519511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.051423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.329498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.620720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.856582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.491507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.872273image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:14.525060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:16.950398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.295666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.708636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.310212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:23.025567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.606241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.141497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.429992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.727010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.944602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.576350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.967673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:14.683407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.044248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.410730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.810359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.414369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:23.183636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.690467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.222453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.527738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:28.814758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:30.041450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.673283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:33.071163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:14.855746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.170372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.514450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:19.918214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.552008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-05-23T14:59:30.145747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.788382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-05-23T14:59:18.623793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-05-23T14:59:17.348536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.726204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:20.430225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.790884image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:23.646654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:24.953970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.508857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.831256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.094783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:30.719688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:31.970580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:33.365044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:15.854547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:17.437049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:18.822467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:20.534201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:21.914524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:23.790460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:25.368407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:26.612236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:27.918223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:29.188055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:30.807686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-23T14:59:32.067532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-05-23T14:59:39.008675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AlcoholAshAsh_AlcanityColor_IntensityFlavanoidsHueMagnesiumMalic_AcidNonflavanoid_PhenolsOD280ProanthocyaninsProlineTotal_Phenols
Alcohol1.0000.232-0.3110.6390.277-0.0250.3530.128-0.1560.0920.1890.6250.295
Ash0.2321.0000.3710.2860.073-0.0460.3500.2240.146-0.0000.0150.2410.127
Ash_Alcanity-0.3110.3711.000-0.077-0.449-0.366-0.1640.3280.386-0.319-0.264-0.469-0.383
Color_Intensity0.6390.286-0.0771.000-0.059-0.4270.3600.2980.066-0.330-0.0380.456-0.000
Flavanoids0.2770.073-0.449-0.0591.0000.5380.221-0.335-0.5380.7540.7300.4150.876
Hue-0.025-0.046-0.366-0.4270.5381.0000.046-0.552-0.2640.4950.3370.2080.440
Magnesium0.3530.350-0.1640.3600.2210.0461.0000.058-0.2360.0540.1660.5030.235
Malic_Acid0.1280.2240.3280.298-0.335-0.5520.0581.0000.260-0.267-0.244-0.066-0.291
Nonflavanoid_Phenols-0.1560.1460.3860.066-0.538-0.264-0.2360.2601.000-0.486-0.387-0.267-0.442
OD2800.092-0.000-0.319-0.3300.7540.4950.054-0.267-0.4861.0000.5820.2530.696
Proanthocyanins0.1890.015-0.264-0.0380.7300.3370.166-0.244-0.3870.5821.0000.3010.667
Proline0.6250.241-0.4690.4560.4150.2080.503-0.066-0.2670.2530.3011.0000.405
Total_Phenols0.2950.127-0.383-0.0000.8760.4400.235-0.291-0.4420.6960.6670.4051.000

Missing values

2025-05-23T14:59:33.523694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-23T14:59:33.655320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AlcoholMalic_AcidAshAsh_AlcanityMagnesiumTotal_PhenolsFlavanoidsNonflavanoid_PhenolsProanthocyaninsColor_IntensityHueOD280Proline
014.231.712.4315.61272.803.060.282.295.641.043.921065
113.201.782.1411.21002.652.760.261.284.381.053.401050
213.162.362.6718.61012.803.240.302.815.681.033.171185
314.371.952.5016.81133.853.490.242.187.800.863.451480
413.242.592.8721.01182.802.690.391.824.321.042.93735
514.201.762.4515.21123.273.390.341.976.751.052.851450
614.391.872.4514.6962.502.520.301.985.251.023.581290
714.062.152.6117.61212.602.510.311.255.051.063.581295
814.831.642.1714.0972.802.980.291.985.201.082.851045
913.861.352.2716.0982.983.150.221.857.221.013.551045
AlcoholMalic_AcidAshAsh_AlcanityMagnesiumTotal_PhenolsFlavanoidsNonflavanoid_PhenolsProanthocyaninsColor_IntensityHueOD280Proline
16813.582.582.6924.51051.550.840.391.548.6600000.741.80750
16913.404.602.8625.01121.980.960.271.118.5000000.671.92630
17012.203.032.3219.0961.250.490.400.735.5000000.661.83510
17112.772.392.2819.5861.390.510.480.649.8999990.571.63470
17214.162.512.4820.0911.680.700.441.249.7000000.621.71660
17313.715.652.4520.5951.680.610.521.067.7000000.641.74740
17413.403.912.4823.01021.800.750.431.417.3000000.701.56750
17513.274.282.2620.01201.590.690.431.3510.2000000.591.56835
17613.172.592.3720.01201.650.680.531.469.3000000.601.62840
17714.134.102.7424.5962.050.760.561.359.2000000.611.60560